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An Agnostic Benchmark for Optical Remote Sensing Image Super-Resolution - MaRDI portal

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An Agnostic Benchmark for Optical Remote Sensing Image Super-Resolution

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DOI10.5281/zenodo.7612255Zenodo7612255MaRDI QIDQ6678845

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 23 January 2023

Copyright license: No records found.



Description

In remote sensing, image super-resolution (ISR) is a technique used to create high-resolution (HR) images from low-resolution (R) satellite images, giving a more detailed view of the Earths surface. However, with the constant development and introduction of new ISR algorithms, it can be challenging to stay updated on the latest advancements and evaluate their performance objectively. To address this issue, we introduce SRcheck, a Python package that provides an easy-to-use interface for comparing and benchmarking various ISR methods. SRcheck includes a range of datasets that consist of high-resolution and low-resolution image pairs, as well as a set of quantitative metrics for evaluating the performance of SISR algorithms.






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